def test_sellar_mdf_COBYLA(self):
prob = Problem()
model = prob.model = SellarDerivativesGrouped()
prob.driver = ScipyOptimizeDriver()
prob.driver.options['optimizer'] = 'COBYLA'
prob.driver.options['tol'] = 1e-9
prob.driver.options['disp'] = False
model.add_design_var('z',
lower=np.array([-10.0, 0.0]),
upper=np.array([10.0, 10.0]))
model.add_design_var('x', lower=0.0, upper=10.0)
model.add_objective('obj')
model.add_constraint('con1', upper=0.0)
model.add_constraint('con2', upper=0.0)
prob.setup(check=False, mode='rev')
failed = prob.run_driver()
self.assertFalse(
failed,
"Optimization failed, result =\n" + str(prob.driver.result))
assert_rel_error(self, prob['z'][0], 1.9776, 1e-3)
assert_rel_error(self, prob['z'][1], 0.0, 1e-3)
assert_rel_error(self, prob['x'], 0.0, 1e-3)
def test_sellar_grouped(self):
# Tests basic Newton solution on Sellar in a subgroup
prob = om.Problem(model=SellarDerivativesGrouped(nonlinear_solver=om.NewtonSolver(solve_subsystems=False)))
prob.setup()
prob.set_solver_print(level=0)
prob.run_model()
assert_near_equal(prob.get_val('y1'), 25.58830273, .00001)
assert_near_equal(prob.get_val('y2'), 12.05848819, .00001)
# Make sure we aren't iterating like crazy
self.assertLess(prob.model.nonlinear_solver._iter_count, 8)
def test_sellar_grouped(self):
# Tests basic Newton solution on Sellar in a subgroup
prob = Problem(model=SellarDerivativesGrouped(nonlinear_solver=NewtonSolver()))
prob.setup(check=False)
prob.set_solver_print(level=0)
prob.run_model()
assert_rel_error(self, prob['y1'], 25.58830273, .00001)
assert_rel_error(self, prob['y2'], 12.05848819, .00001)
# Make sure we aren't iterating like crazy
self.assertLess(prob.model.nonlinear_solver._iter_count, 8)
def test_basic(self):
prob = Problem()
model = prob.model = SellarDerivativesGrouped()
prob.driver = pyOptSparseDriver()
prob.driver.options['optimizer'] = "SLSQP"
model.add_design_var('z', lower=np.array([-10.0, 0.0]), upper=np.array([10.0, 10.0]))
model.add_design_var('x', lower=0.0, upper=10.0)
model.add_objective('obj')
model.add_constraint('con1', upper=0.0)
model.add_constraint('con2', upper=0.0)
prob.set_solver_print(level=0)
prob.setup(check=False, mode='rev')
prob.run_driver()
assert_rel_error(self, prob['z'][0], 1.9776, 1e-3)
def test_sellar_derivs_grouped(self):
# Test derivatives across a converged Sellar model.
prob = Problem()
prob.model = SellarDerivativesGrouped()
prob.model.linear_solver = self.linear_solver_class()
prob.set_solver_print(level=0)
mda = prob.model.get_subsystem('mda')
prob.setup(check=False, mode='fwd')
prob.run_model()
# Just make sure we are at the right answer
assert_rel_error(self, prob['y1'], 25.58830273, .00001)
assert_rel_error(self, prob['y2'], 12.05848819, .00001)
wrt = ['x', 'z']
of = ['obj', 'con1', 'con2']
Jbase = {}
Jbase['con1', 'x'] = [[-0.98061433]]
Jbase['con1', 'z'] = np.array([[-9.61002285, -0.78449158]])
Jbase['con2', 'x'] = [[0.09692762]]
Jbase['con2', 'z'] = np.array([[1.94989079, 1.0775421]])
Jbase['obj', 'x'] = [[2.98061392]]
Jbase['obj', 'z'] = np.array([[9.61001155, 1.78448534]])
J = prob.compute_totals(of=of, wrt=wrt, return_format='flat_dict')
for key, val in iteritems(Jbase):
assert_rel_error(self, J[key], val, .00001)
prob.setup(check=False, mode='rev')
prob.run_model()
J = prob.compute_totals(of=of, wrt=wrt, return_format='flat_dict')
for key, val in iteritems(Jbase):
assert_rel_error(self, J[key], val, .00001)
def test_sellar_mdf(self):
prob = Problem()
model = prob.model = SellarDerivativesGrouped()
prob.driver = pyOptSparseDriver()
prob.driver.options['optimizer'] = OPTIMIZER
if OPTIMIZER == 'SNOPT':
prob.driver.opt_settings['Verify level'] = 3
prob.driver.options['print_results'] = False
model.add_design_var('z', lower=np.array([-10.0, 0.0]), upper=np.array([10.0, 10.0]))
model.add_design_var('x', lower=0.0, upper=10.0)
model.add_objective('obj')
model.add_constraint('con1', upper=0.0)
model.add_constraint('con2', upper=0.0)
prob.setup(check=False, mode='rev')
prob.run_driver()
assert_rel_error(self, prob['z'][0], 1.9776, 1e-3)
assert_rel_error(self, prob['z'][1], 0.0, 1e-3)
assert_rel_error(self, prob['x'], 0.0, 1e-3)
